The impact of a Canadian external Employee Assistance Program on mental health and workplace functioning: Findings from a prospective quasi-experimental study
Bibliographic record
Abstract
In this investigation, a quasi-experimental prospective evaluation employing a pretest–posttest control group design with propensity score matching estimated the causal impacts of a Canadian Employee Assistance Program (EAP) on mental health, workplace functioning, and life satisfaction. Participants (N = 304) were employees working at different organizations across Canada. EAP users had access to up to 12 counseling hours per year. Outcomes were compared between groups of EAP (n = 152) and non-EAP (n = 152) users matched on numerous baseline variables including demographic, occupational, mental health, workplace functioning, and other characteristics and measures. At 6 month follow-up, EAP users had significantly reduced psychological distress, including reduced symptoms of depression and anxiety compared to non-EAP users. EAP users also had significantly reduced work presenteeism and work distress, and increased work engagement. Finally, they reported greater life satisfaction at follow-up relative to non-EAP users. The largest effect sizes of EAP counseling were observed on mental health outcomes. Mediation analyses revealed that EAP treatment effects on workplace functioning were mediated by changes in (their positive impacts on) mental health. This is the first known quasi-experimental study conducted with an external EAP, with evidence supporting a causal link between use of a Canadian assistance program and a number of positive clinical and workplace outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".